With over 2 billion people around the world now users of a smartphone, we have more computing power than ever right at our fingertips than ever before. Our cars, houses, factories, cities, etc. are all becoming smarter too. With all of this distributed computing power and applications, we’re producing and consuming vast quantities of data … but are we using this data effectively?
As systems grow in complexity and the number of connected devices/sensors increases, so too does the sheer volume of data produced. That is a lot of (potentially sensitive) data to be sending to the cloud to be analyzed for faults/abnormalities. Then there is the issue of network connectivity: what if the network goes down? What if the latency is too high for the safety/mission/business critical scenario? There are many single points of failure in a cloud-reliant solution. Local computing is therefore still vitally important to many industries, but this data still has value. Aggregating this data at the edge for cloud analysis is one way in which companies can derive massive business benefits without overburdening network communications. This aggregate data can be analyzed for insights, and results deployed back down to the edge.
Automation is an area in which edge computing plays a vital role: when you need an action to be taken immediately should something happen; you require a low-latency instantaneous response. Running edge based analytics enables companies to perform reactive, predictive, and prescriptive actions in real-time with no bandwidth costs or WAN networking issues to worry about. Automating decisions at the edge enables geographically isolated systems to benefit from big-data analytics without requiring high-bandwidth, low-latency connections to the cloud.
Edge computing is enabling many areas of high interest: self-driving cars, factory automation, autonomous drones, predictive maintenance, and the list keeps growing. Unlocking the potential of the ever-growing volume of data being produced means greater efficiency, more effective and timely actions, and valuable insights.
The recently announced Vortex Edge PMQ solution utilizes the power of PrismTech’s Vortex data-connectivity software, ADLINK’s ruggedized industrial hardware, and IBM’s advanced Predictive Maintenance and Quality analytics. Vortex Edge PMQ provides an edge analytics solution designed for Industrial Internet of Things environments where cloud computing access may be limited or otherwise not desired.
For a more detailed look at Vortex Edge PMQ and implementation examples, visit http://www.prismtech.com/vortex/vortex-edge-pmq